Publications associées à From basic sciences and engineering to epileptology: A translational approach

Publications associées (38)

A Spatiotemporal Analysis of Brain Dynamics, a New Feature for Sleep and Seizure State Discrimination

The human brain is a complex and dynamic physiological system that can be considered as a network of reciprocally interconnected systems localized in different brain regions. To fully characterize the brain's complex dynamics, it is essential to investigat ...

IEEE2025

Capturing behavioral and neural variability in multi-area spiking neuronal network models

Christos Sourmpis

How does the brain generate behavioral responses from sensory stimuli? This sensor-to-motor transformation is a fundamental question in systems neuroscience. While recent experiments have highlighted the complexity of neural representations across the cere ...

EPFL2025

Integrated Wireless Power, Data Communication, and Thermal Sensing System for Autonomous Multisite Brain Implants

Mohammad Javad Karimi

Implanted medical devices (IMDs) have been widely developed to support the monitoring and recording of biological data inside the body or brain. Wirelessly powered IMDs, a subset of implantable electronics, have been proposed to eliminate the limitations r ...

EPFL2024

Effects of multidisciplinary inpatient rehabilitation on everyday life physical activity and gait in patients with multiple sclerosis

Kamiar Aminian, Anisoara Ionescu, Gaëlle Prigent

Background Multiple sclerosis is a progressive neurological disease that affects the central nervous system, resulting in various symptoms. Among these, impaired mobility and fatigue stand out as the most prevalent. The progressive worsening of symptoms ad ...

BioMed Central2024

Comparing various AI approaches to traditional quantitative assessment of the myocardial perfusion in [82Rb] PET for MACE prediction

Adrien Raphaël Depeursinge, Julien René Fageot

Assessing the individual risk of Major Adverse Cardiac Events (MACE) is of major importance as cardiovascular diseases remain the leading cause of death worldwide. Quantitative Myocardial Perfusion Imaging (MPI) parameters such as stress Myocardial Blood F ...

Nature Portfolio2024

Community-based reconstruction and simulation of a full-scale model of region CA1 of rat hippocampus

Henry Markram, Felix Schürmann, James Gonzalo King, Srikanth Ramaswamy, Juan Bautista Hernando Vieites, Alexis Arnaudon, Eilif Benjamin Muller, Michael Reimann, Huanxiang Lu, Ying Shi, Marwan Muhammad Ahmed Abdellah, Vishal Sood, Jean-Denis Georges Emile Courcol, Werner Alfons Hilda Van Geit, Lida Kanari, Michael Emiel Gevaert, Pramod Shivaji Kumbhar, Liesbeth Maria L Vanherpe, Armando Romani, Cyrille Pierre Henri Favreau, Mohameth François Sy, Judit Planas Carbonell, Genrich Ivaska, András Ecker, Alberto Antonietti, Cristina Colangelo, Anna-Kristin Kaufmann, Julian Martin Budd, Thomas Brice Delemontex, Davide Bella, Fabien Petitjean, Nadir Roman Guerrero, Mustafa Kerem Kurban, Joni Henrikki Herttuainen, Pranav Rai, Elvis Boci

The CA1 region of the hippocampus is one of the most studied regions of the rodent brain, thought to play an important role in cognitive functions such as memory and spatial navigation. Despite a wealth of experimental data on its structure and function, i ...

2024

Generalization and Personalization of Machine Learning for Multimodal Mobile Sensing in Everyday Life

Lakmal Buddika Meegahapola

A range of behavioral and contextual factors, including eating and drinking behavior, mood, social context, and other daily activities, can significantly impact an individual's quality of life and overall well-being. Therefore, inferring everyday life aspe ...

EPFL2024

Changes in spatial self-consciousness elicit grid cell–like representation in the entorhinal cortex

Olaf Blanke, Hyeongdong Park, Hyukjun Moon, Baptiste Gauthier, Emanuela De Falco, Louis Philippe Albert

Grid cells in the entorhinal cortex (EC) encode an individual’s location in space, integrating both environmental and multisensory bodily cues. Notably, body-derived signals are also primary signals for the sense of self. While studies have demonstrated th ...

2024

Voices from the Frontline: Revealing the AI Practitioners' viewpoint on the European AI Act

Kathrin Grosse

Artificial intelligence (AI) is increasingly used in an ever larger number of industries. Alongside this development, however, abundant works argue that AI-driven systems are lacking in terms of safety, ethics and transparency. As a direct consequence, the ...

2024

Robust machine learning for neuroscientific inference

Steffen Schneider

Modern neuroscience research is generating increasingly large datasets, from recording thousands of neurons over long timescales to behavioral recordings of animals spanning weeks, months, or even years. Despite a great variety in recording setups and expe ...

EPFL2024

Task-driven neural network models predict neural dynamics of proprioception: Experimental data, activations and predictions of neural network models

Axel Bisi, Alberto Silvio Chiappa, Alexander Mathis, Alessandro Marin Vargas

Here we provide the neural data, activation and predictions for the best models and result dataframes of our article "Task-driven neural network models predict neural dynamics of proprioception". It contains the behavioral and neural experimental data (cu ...

EPFL Infoscience2024

Development and clinical validation of computational imaging biomarkers for neurodegenerative diseases

Veronica Lily Ravano

Neurodegenerative and neuroinflammatory disorders often involve complex pathophysiological mechanisms that are â to this date â only partially understood. A more comprehensive understanding of those microstructural processes and their characterization ...

EPFL2024

Reliable data-driven decision-making through optimal transport

Bahar Taskesen

Decision-making permeates every aspect of human and societal development, from individuals' daily choices to the complex decisions made by communities and institutions. Central to effective decision-making is the discipline of optimization, which seeks th ...

EPFL2024

Magnetic structure and magnetoelectric properties of the spin-flop phase in LiFePO4

Sofie Janas, Ellen Fogh, Paola Caterina Forino

We investigate the magnetic structure and magnetoelectric(ME) effect in the high -field phase of the antiferromagnet LiFePO 4 above the critical field of 31 T. A neutron diffraction study in pulsed magnetic fields reveals the propagation vector to be q = 0 ...

Amer Physical Soc2024

Neuroengineering of hallucinations through fMRI neurofeedback: Understanding and modulating neural dynamics for the control of hallucinations in health and disease

Herberto Dhanis Pedro De Barros Camacho

Recent years have seen considerable progress in understanding brain function, and in modulating it through real-time fMRI neurofeedback (NF). Inspired by these advances, paired with the unique possibility of inducing the clinically relevant Presence Halluc ...

EPFL2023

Task matters: Individual MEG signatures from naturalistic and neurophysiological brain states

Alessandra Griffa, Enrico Amico, Ekansh Sareen

The discovery that human brain connectivity data can be used as a "fingerprint " to identify a given individual from a population, has become a burgeoning research area in the neuroscience field. Recent studies have iden-tified the possibility to extract t ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2023

Arbitrary Decisions are a Hidden Cost of Differentially Private Training

Bogdan Kulynych, Carmela González Troncoso

Mechanisms used in privacy-preserving machine learning often aim to guarantee differential privacy (DP) during model training. Practical DP-ensuring training methods use randomization when fitting model parameters to privacy-sensitive data (e.g., adding Ga ...

Assoc Computing Machinery2023

Brain dynamics uncovered using a machine-learning algorithm

Mackenzie Mathis

CEBRA is a machine-learning method that can be used to compress time series in a way that reveals otherwise hidden structures in the variability of the data. It excels at processing behavioural and neural data recorded simultaneously, and it can decode act ...

NATURE PORTFOLIO2023

Harmonization of multi-scanner in vivo magnetic resonance spectroscopy: ENIGMA consortium task group considerations

Cristina Ramona Cudalbu Moldovan

Magnetic resonance spectroscopy is a powerful, non-invasive, quantitative imaging technique that allows for the measurement of brain metabolites that has demonstrated utility in diagnosing and characterizing a broad range of neurological diseases. Its impa ...

FRONTIERS MEDIA SA2023

Neurotechnologies to restore hand functions

Solaiman Shokur, Silvestro Micera

Reaching and manipulating objects are crucial tasks that allow proactive interaction with our surroundings. However, these functions are lost after neurological disorders or traumatic events that cause hand paralysis. Neuroprosthetic technologies are medic ...

SPRINGERNATURE2023